This paper introduces the concepts of amount and speed of a discounting procedure in order to generate well-characterized families of procedures for use in social project evaluation. Exponential discounting sequesters the concepts of amount and speed into a single parameter that needs to be disaggregated in order to characterize nonconstant rate procedures. The inverse of the present value of a unit stream of benefits provides a natural measure of the amount a procedure discounts the future. We propose geometrical and time horizon based measures of how rapidly a discounting procedure acquires its ultimate present value, and we prove these to be the same. This provides an unambiguous measure of the speed of discounting, a measure whose values lie between 0 (slow) and 2 (fast). Exponential discounting has a speed of 1. A commonly proposed approach to aggregating individual discounting procedures into a social one for project evaluation averages the individual discount functions. We point to serious shortcoming with this approach and propose an alternative for which the amount and time horizon of the social procedure are the averages of the amounts and time horizons of the individual procedures. We further show that the social procedure will in general be slower than the average of the speeds of the individual procedures. For potential applications in social project evaluation we characterize three families of two-parameter discounting procedures – hyperbolic, gamma, and Weibull – in terms of their discount functions, their discount rate functions, their amounts, their speeds and their time horizons. (The appendix characterizes additional families, including the quasi-hyperbolic one.) A one parameter version of hyperbolic discounting, d(t) = (1+rt)-2, has amount r and speed 0, and this procedure is our candidate for use in social project evaluation, although additional empirical work will be needed to fully justify a one-parameter simplification of more general procedures.

In order to be sensible about what discount rate to use one must be clear about its purpose. We suggest that its purpose is to help select those projects that will contribute more net benefits than some other discount rate. This approach, which is after all the foundation for benefit-cost analysis, helps to reconcile different suggested procedures for determining the discount rate. We suggest that the social opportunity cost of capital (SOC) is superior to other suggested approaches in its generality and its ease of use. We use the SOC to determine a range of real rates that vary between 6% and 8%. We suggest that approaches based on determination of preferences, which result in hyperbolic discounting, are less appropriate and less useful.

For more than 40 years, governments and professional associations have acted, voted or lobbied against the implementation of the Community Patent (COMPAT, officially called the EU Patent). The econometric results and simulations presented in this paper suggest that, thanks to its attractiveness in terms of market size and a sound renewal fee structure, the COMPAT would drastically reduce the relative patenting costs for applicants while generating more income for the European Patent Office and most National Patent Offices. The loss of economic rents (€400 million would be lost by patent attorneys, translators and lawyers) and the drop of controlling power by national patent offices elucidate further the observed resistance to the Community Patent.

We evaluate the impact of three auction mechanisms—the Becker-DeGroot-Marschak (BDM) mechanism, the second-price auction (SPA), and the random nth-price auction (NPA)—in the measurement of private willingness-to-pay and willingness-to-accept for a pure public good. Our results show that the endowment effect is lower with the BDM mechanism. In this market mechanism, the effect disappears after a few repetitions. Yet, on a logarithmic scale, the random nth-price auction yields the highest speed of convergence towards equality of welfare indices. We also observe that subjects value public goods in reference to their private subjective benefit derived from their public funding.

As traditionally conducted, benefit-cost analysis is rooted in neoclassical welfare economics, which, in its most simplified form, assumes that individuals act rationally and are primarily motivated by self-interest, making decisions that maximize their welfare. Its conduct is evolving to reflect recent work in behavioral economics, which explores the psychological aspects of decisionmaking. We consider several implications for analyses of social programs, focusing largely on economic valuation. First, benefit-cost analysis often involves valuing nonmarket outcomes such as reductions in health and environmental risks. Behavioral research emphasizes the need to recognize that these values are affected by psychological as well as physical attributes. Second, benefit-cost analysis traditionally uses exponential discounting to reflect time preferences, while behavioral research suggests that individuals’ discounting may be hyperbolic. While the appropriate rates and functional form are uncertain, market rates best represent the opportunity costs associated with diverting funds to support a particular social policy or program. Such rates reflect the intersection between technological progress and individual preferences, regardless of whether these preferences fit the standard economic model or a behavioral alternative. Third, behavioral research emphasizes the need to consider the influence of other-regarding preferences on valuation. In addition to acting altruistically, individuals may act reciprocally to reward or punish others, or use the status of others as the baseline against which to assess their own well-being. Fourth, behavioral economics identifies factors that can help researchers develop valuation studies that provide well-informed, thoughtful preferences. Finally, while behavioral research has led some to argue for a more paternalistic approach to policy analysis, an alternative is to continue to focus on describing the preferences of those affected by the policy options while working to ensure that these preferences are based on knowledge and careful reflection. Benefit-cost analysis can be best viewed as a pragmatic framework for collecting, organizing, and evaluating relevant information.

An understanding of the uncertainty in benefit and cost estimates is a critical part of a benefit–cost analysis. Without a quantitative treatment of uncertainty, it is difficult to know how much confidence to place in the benefit–cost estimates associated with regulatory analysis. In 2002, an NRC report recommended that EPA move toward conducting probabilistic, multiple-source uncertainty analyses in its RIAs with the specification of probability distributions for major sources of uncertainty in the benefit estimates. In 2006, reports by GAO and RFF found that EPA had begun to address the NRC recommendations, but that much remained to be done to meet the NRC concerns. This paper provides a further review of EPA’s progress in developing a quantitative assessment of the uncertainties in its health benefits analyses for the RIAs for four recent rulemakings setting National Ambient Air Quality Standards (NAAQS). In conclusion, EPA’s basic approach to presenting the uncertainty in its health benefits estimates remains largely unchanged. Recent RIAs present the results of uncertainty analysis in piecemeal fashion rather than providing an overall, comprehensive statement of the uncertainty in the estimates. In addition, the uncertainty analysis in recent RIAs continues to focus on the concentration-response relationship and largely fails to address the uncertainty associated with the other key elements of the benefits analysis.

We summarize procedures for assessing the benefits and costs of using labor inputs in public projects. Examples are provided to illustrate how information on labor inputs can be analyzed and presented such that, should the analyst choose, labor services generate elements of both benefit and cost in times of high unemployment; however, this is not generally correct in times of full employment. Our analysis is consistent with the overall goal of identifying those projects which are estimated to improve efficiency—those with social benefits in excess of social costs.